Systems biology approaches to understand gene specification networks in the zebrafish retina

The ontogeny of the vertebrate retina has been a topic of interest to developmental biologists and human geneticists for many decades. Understanding the unfolding of the genetic program that transforms a field of progenitors' cells into a functionally complex and multi-layered sensory organ is a formidable challenge. Although classical genetic studies succeeded in identifying the key regulators of retina specification, we are far from understanding the architecture of their gene regulatory networks (GRNs) and thus from predicting their behaviour. A goal in our group during the last years has been to analyse the bifurcation of the GRNs specifying the neural retina and RPE domains, as cells in these two compartments acquire their distinct shape; within a few hours window in zebrafish. We have characterized transcriptome dynamics and chromatin accessibility in segregating NR/RPE populations in zebrafish to identify active cis-regulatory modules and enriched TF motives within them (Buono et al Nat com 2021). We have shown extensive network redundancy and context-dependent activity for the core TFs within each domain. In line with this finding, we have shown that the simultaneous mutation of the key specifiers vsx1 and vsx2 by CRISPR/Cas9, which results in severe visual impairment and bipolar cells depletion, does not interfere with neural retina specification. We concluded that although important cis-regulatory remodelling (ATAC-seq) occurs in vsxKO retinas during early specification, this has little impact at a transcriptomic level (RNA-seq). Our observations point to genetic redundancy as an important mechanism sustaining the integrity of the retinal specification network (Letelier & Buono et al Biorxiv 2022). We are currently complementing previous efforts by applying single-cell methods to the analysis of neural retina and RPE networks. We have generated transcriptome and epigenome (chromium 10x multiome scRNAseq¿+¿scATACseq) datasets in zebrafish to obtain predicti